Glioma Stem Cell–Specific Superenhancer Promotes Polyunsaturated Fatty-Acid Synthesis to Support EGFR Signaling

Glioblastoma is the most prevalent primary intrinsic brain tumor in adults, has a median survival of less than 15 months, and is universally lethal despite maximal therapy (1). Recent investigation of cancer stem cells, a subset of tumor cells proposed to sustain tumorigenesis and cellular heterogeneity (2), has contributed to an improved understanding of this deadly cancer. Although there has been controversy surrounding the origins and defining molecular characteristics of cancer stem cells, functionally defined glioma stem cells (GSC) promote glioblastoma pathogenesis and contribute to the suboptimal efficacy of current treatment options through mediating angiogenesis (3), resistance to radiotherapy (4) and chemotherapy (5), invasion into normal brain (6), and self-renewal (7). These characteristics implicate GSCs as important targets for the design of novel therapeutics for glioblastoma.

Although glioblastoma and other cancers have traditionally been viewed as genetic diseases, epigenetic alterations play an important role in cancer pathogenesis and progression. In glioblastomas and other brain tumors, epigenome and chromatin regulators are frequently disrupted and promote malignant phenotypes (8, 9). As therapeutics targeting genomic drivers have been, at best, marginally effective for glioblastoma, new therapeutic paradigms that integrate the epigenetic state of GSCs may yield benefit. Superenhancers, defined as regulatory regions with unusually strong enrichment for the binding of transcriptional coactivators, function as master epigenetic regulators that define cell state, regulate genes controlling cell identity, orchestrate cell type–dependent transcriptional networks, and are enriched for disease-associated genetic variation (10–12). We hypothesized that interrogation of superenhancer profiles may provide insight into the cell type–specific molecular processes that underlie GSC maintenance, identify cancer dependency genes and genetic programs critical to glioma initiation and progression, and translate into new therapeutic strategies.

Cancer cells co-opt aberrant metabolic networks to gain proliferative advantages through a number of avenues. In diffuse glioma, IDH1 and IDH2 mutations are critical tumor-initiating events that establish altered metabolic networks that drive widespread epigenetic reprogramming through establishment of a glioma CpG-island methylator phenotype (G-CIMP; refs. 13, 14). In other cancers, altered lipid metabolism and fatty-acid synthesis are also important for metabolic reprogramming (15). Lipid composition is greatly altered in gliomas with enrichment for free fatty acids and polyunsaturated fatty acids (16). Cholesterol uptake, synthesis, and signaling features are key dependencies of GSCs and have been the targets of therapeutic development efforts (17–20). Aberrant EGFR and other receptor tyrosine kinase (RTK) signaling pathways, which are commonly dysregulated in glioma, drive a metabolic shift favoring fatty-acid synthesis and a dependence on this enhanced lipogenesis (21–23). Thus, we utilized an unbiased cell state–dependent superenhancer profiling approach to identify epigenetically driven oncogenes and investigated the underlying regulatory networks that drive expression of these genes and their role in GSC biology.

To identify GSC-specific superenhancers in an unbiased manner, we utilized an in silico superenhancer target selection strategy to identify superenhancer-associated genes present within glioblastoma surgical specimens that overlapped with stem state–specific enhancers (Fig. 1A). We profiled the epigenetic landscape of 10 glioblastoma surgical resection samples and 15 normal brain samples through H3K27ac ChIP-seq (histone 3 lysine 27 acetylation chromatin immunoprecipitation followed by next-generation sequencing) datasets that we and others generated (19, 24, 25). Both typical enhancer and superenhancer analyses revealed that samples clustered together based on disease status (Fig. 1B–D), suggesting that glioblastoma specimens contained unique epigenetic landscapes that promote tumorigenesis. Annotation of superenhancer regions to the nearest gene across 10 glioblastoma primary tissue samples identified a number of consistent targets, including EGFR, SOX2, CTDSP2, MIR9-1, and POU3F3 (Supplementary Fig. S1A). We focused on superenhancers specific to glioblastoma compared with normal brain samples (Fig. 1E). To identify superenhancers with potential stem-state specificity, we compared the epigenetic landscape of three human patient–derived GSCs with three matched serum-differentiated glioma cells (DGC) through analysis of H3K27ac ChIP-seq data (ref. 26; Fig. 1F). This approach permitted identification of cell state–specific epigenetically upregulated gene networks in identical genetic backgrounds. GSC-specific constituent enhancers of glioblastoma-specific superenhancers displayed enrichment for transcriptional motifs of OCT4, NR2E1, and several SOX family members, which are important in GSC biology (Fig. 1G). A total of 148 superenhancer-associated genes were identified using this method and were assigned a “GSC specificity score” based on (i) the number of gained H3K27ac peaks in the GSC samples compared with DGC samples and (ii) the mRNA expression difference between GSC and DGC samples (Fig. 1H). Neurogenesis, nervous system development pathways, and pathways involved in oligodendrocyte and cellular differentiation processes were enriched in these GSC-specific superenhancer-associated genes (Fig. 1I). To prioritize these genes for further study, we selected genes with (i) prognostic significance in The Cancer Genome Atlas (TCGA) database, where high gene expression was associated with poor glioblastoma patient survival in either IDH wild-type or IDH-mutant glioblastomas (Supplementary Fig. S1B–S1D) and (ii) elevated expression in glioblastoma tissue versus normal brain tissue from integrated analyses of the TCGA and GTEx databases (Fig. 1J; Supplementary Fig. S1E). Fewer genes carried prognostic significance when restricted to IDH wild-type glioblastomas (Supplementary Fig. S1C). The three top-ranked genes (WSCD1, ELOVL2, and KLHDC8A) were selected for further validation and analyses (Fig. 1K).

To validate the role of genes marked by superenhancers in glioblastoma biology, we interrogated the roles of these relatively uncharacterized genes in GSC biology. WSCD1, ELOVL2, and KLHDC8A were each marked by a super-enhancer specific for glioblastoma and GSCs (Fig. 2A–C), portended a negative prognosis in glioblastoma, and were overexpressed in glioblastoma surgical tissues compared with normal brain (Fig. 2D–F). Each superenhancer-associated gene was upregulated in glioblastoma cells compared with other tumor cellular components, including astrocytes, oligodendrocytes, and immune cell fractions in single-cell RNA sequencing (scRNA-seq) datasets (ref. 27; Fig. 2G–I). In a validation panel of seven patient-derived GSCs, ELOVL2, KLHDC8A, and WSCD1 mRNA levels were increased in GSCs compared with their differentiated tumor counterparts (Fig. 2J–L). Differentiation of DGCs was validated by detecting decreased mRNA levels of SOX2 and OLIG2 and increased mRNA levels of GFAP compared with GSCs (Supplementary Fig. S2A–C). These findings were verified using two independent biological replicates (Supplementary Fig. S2D–S2I). Defining the precise gene targets of superenhancers remains an unresolved challenge. Several factors complicate this task: (i) enhancers can regulate more than a single gene; (ii) chromosomal looping events can lead to enhancer–gene pairs that are distant in the linear DNA sequence; and (iii) enhancers may function in a cell type–specific manner (28). Superenhancers depend on the binding of transcriptional coactivators, including BRD4, to drive downstream gene expression. Inhibition of BRD4 with JQ1 blocks transcriptional coactivation effects and specifically diminishes expression of superenhancer-driven genes (29, 30). We treated three patient-derived GSC lines with JQ1 and observed diminished mRNA levels of ELOVL2 and KLHDC8A, along with a positive control gene (MYC), in three GSCs (Supplementary Figs. S2J–S2M), supporting ELOVL2 and KLHDC8A as driven by stem cell–specific superenhancers. Knockdown of the superenhancer-associated genes with two independent nonoverlapping shRNAs per gene inhibited cell proliferation of two patient-derived GSC lines (GSC387 and GSC3565; Fig. 2M–O; Supplementary Fig. S2N–S2P). Collectively, these results confirm that these superenhancer-regulated genes are essential for GSC maintenance. We interrogated the role of ELOVL2 in GSC biology, as among the genes tested, ELOVL2 most robustly stratified patients based on prognosis, demonstrated responsiveness to JQ1, and may be amenable to therapeutic targeting due to its role as an enzyme.

To functionally dissect drivers of the putative ELOVL2 superenhancer, we analyzed available GSC ChIP-seq data (26) and found that two essential neurodevelopmental and stem-cell transcription factors, SOX2 and OLIG2, bound within a 500-bp region of the ELOVL2 superenhancer in GSCs, overlapping with a region of open chromatin and characterized by a relative minimum in H3K27ac signal (Fig. 3A). In clinical samples from TCGA, ELOVL2 expression positively correlated with expression of SOX2 and OLIG2 in the classic subtype of glioblastoma (Fig. 3B), which is characterized by EGFR activity. In direct ChIP-PCR studies, SOX2 binding was enriched in three patient-derived GSCs at this locus compared with a negative control region (Fig. 3C). Furthermore, knockdown of SOX2 with three independent nonoverlapping shRNAs diminished expression of ELOVL2 (Fig. 3D). To assess the functional regulatory role of this locus and the superenhancer region, we recruited a transcriptional repressor complex (KRAB) to this noncoding region using a catalytically dead CRISPR/Cas9 system (dCas9; Fig. 3E), which inhibited ELOVL2 expression at the mRNA level following recruitment of the dCas9–KRAB complex (Fig. 3F). Silencing of the superenhancer component contributed to a cell proliferation defect (Fig. 3G) and decreased protein levels of ELOVL2 in GSCs to a level more consistent with that of a differentiated glioma cell (Fig. 3H–J). Collectively, these findings indicate that this superenhancer element drives expression of ELOVL2, with contributions from the stem state–specific transcription factor SOX2.

To generalize the contribution of ELOVL2 in GSCs, ELOVL2 knockdown in four additional patient-derived GSCs confirmed our previous findings of impaired cell proliferation capacity (Fig. 4A; Supplementary Fig. S3A and S3B). To address potential off-target effects associated with shRNAs, we generated an ELOVL2 knockout using CRISPR/Cas9 technology (Supplementary Figs. S3C and S3D), which led to a similar cell proliferation defect in vitro (Fig. 4B). Two additional shRNAs targeting nonoverlapping sequences in the ELOVL2 transcript also impaired cell proliferation (Supplementary Figs. S3E and S3F). Extreme limiting dilution assays (ELDA) are a surrogate for cellular self-renewal capacity. Using an in vitro ELDA, GSC stem cell frequency and self-renewal were diminished following depletion of ELOVL2 in two patient-derived GSCs (Fig. 4C; Supplementary Fig. S3G). ELOVL2 knockdown induced apoptotic cell death in two GSCs, as measured by Annexin V staining (Fig. 4D) and decreased in expression of GSC markers (SOX2 and OLIG2), further supporting a role in the loss of stemness (Supplementary Fig. S3H). ELOVL2 knockdown induced cell-cycle defects, including accumulation of cells in sub-G₀ and G₁ phases (Supplementary Fig. S3I). To address the cell-state dependency for ELOVL2 expression, ELOVL2 was depleted by shRNAs in three patient-derived GSCs following in vitro differentiation, revealing no significant changes in cell proliferation capacity in the differentiated glioma cells (Fig. 4E–G; Supplementary Fig. S3J). Although GSCs underwent apoptosis as indicated by cleaved PARP, matched DGCs display only the uncleaved protein (Fig. 4H–J). Next, we interrogated the potential functional roles of ELOVL2 in nonneoplastic cells. Knockdown of ELOVL2 impaired proliferation of three neural stem cells (Supplementary Fig. S4A), but had minimal impact on nonneoplastic neural cells derived from epilepsy tissue resection specimens (Supplementary Fig. S4B). To further understand the dependency on ELOVL2 across numerous cancer cell types, we interrogated the Cancer Dependency Map (www.depmap.org). Across a panel of 558 cell lines profiled using whole-genome CRISPR/Cas9 screening and 711 cell lines profiled using whole-genome shRNA screening, ELOVL2 was not a pan-essential gene (Supplementary Fig. S4C and S4D). In normal brain profiled by scRNA-seq (31), ELOVL2 colocalizes with SOX2 and is enriched in radial glial and intermediate progenitor cell populations, indicating a possible role in maintenance of stemness (Supplementary Fig. S4E–S4H). Thus, ELOVL2 is critical for the maintenance of GSCs, but is not essential for DGCs or more differentiated nonneoplastic neural cells.

ELOVL2 is an endoplasmic reticulum transmembrane protein that functions in the synthesis of long chain ω3 and ω6 polyunsaturated fatty acids (LC-PUFA). ELOVL2 converts arachidonic acid (ω6-C20:4 AA) and eicosapentaenoic acid (ω3-C20:5 EPA) to the longer chain PUFAs docosapentaenoic acid (ω6-C22:5 DPA) and docosahexaenoic acid (ω3-C22:6 DHA). Mass spectrometry analysis of total fatty-acid levels revealed elevated LC-PUFAs (ω3-DHA and ω6-DPA) in GSCs compared with matched DGCs, suggesting that increased expression of ELOVL2 in GSCs drives elongation to form these intermediate species (Fig. 5A and B). We hypothesized that this metabolic network producing LC-PUFAs is upregulated in GSCs and that disruption impairs GSC viability. In accordance with this model, supplementation of cell culture media with the LC-PUFAs ω3-DHA or ω6-DPA partially rescued the cell proliferation defect caused by ELOVL2 knockdown (Supplementary Fig. S5A and S5B), indicating LC-PUFA deficiency caused by ELOVL2 knockdown contributes to the observed phenotypes. LC-PUFAs play a number of roles including serving as an energy source, acting as a key component of membrane phospholipids, and mediating intracellular signaling via the NFκB, PPAR, and SREBP networks. In addition to nuclear signaling roles, LC-PUFAs are important as a reservoir for eicosanoid production via oxygenation by COX, LOX, and CYP systems. To further narrow the role of ELOVL2 in GSCs, we performed global mass spectrometry–based metabolomic analysis following ELOVL2 knockdown and identified differential metabolites in two patient-derived GSCs in both positive and negative modes (Supplementary Fig. S5C–S5F). Several metabolites were consistently altered following ELOVL2 knockdown (Fig. 5C and D), with enrichment in phosphatidylserine species (Fig. 5E). Pathway analyses of differential metabolites within each GSC demonstrated a consistent enrichment for purine salvage and pyrimidine degradation pathways in GSCs with an associated increase in the purine salvage products hypoxanthine and guanine (Supplementary Figs. S5G–S5J).

As the most consistent trends suggested alterations in phospholipid metabolism, we utilized a mass spectrometry–based shotgun lipidomics approach to gain a more comprehensive view of lipid alterations following ELOVL2 knockdown, revealing (i) an increase in the quantities of phospholipids, including a number of phosphatidylcholine and phosphatidylethanolamine species, and (ii) a reciprocal decrease in several lysophospholipids, including lysophosphoethanolamines (Fig. 5F and G). ELOVL2 knockdown contributed to alteration in transcriptional signatures associated with phospholipid remodeling and phospholipase activity (Fig. 5H; Supplementary Fig. S5K). These findings suggest alterations in the Lands cycle—a series of phospholipase-driven deacylation and lysophospholipid acyltransferase-driven reacylation reactions that synergize to alter phospholipid composition and control membrane asymmetry, diversity, and fluidity. As ELOVL2 knockdown contributed to an altered cellular phospholipid profile, we hypothesized that this change could impair cell membrane structure. Fluorescence recovery after photobleaching (FRAP) assays of cellular membranes showed that ELOVL2 knockdown impaired fluorescence recovery in GSCs, indicating a decrease in cellular membrane fluidity (Fig. 5I–K). Thus, ELOVL2 promotes cellular membrane composition and architecture in GSCs.

To understand the functional consequences of ELOVL2 depletion and its associated signaling networks, we interrogated the TCGA dataset by correlating ELOVL2 mRNA levels to potential downstream signaling proteins measured by reverse-phase protein array (RPPA) in surgical biopsy glioblastoma tissues. This revealed high expression of ELOVL2 strongly associated with key receptor tyrosine kinase signaling elements, including EGFR and activated, phosphorylated EGFR (pY1068 and pY1173; Fig. 6A and B). Upon segregation of the TCGA dataset based on ELOVL2 expression, EGFR mRNA was one of the most differentially expressed genes (Supplementary Fig. S6A). Reciprocally, ELOVL2 was one of the most differentially expressed genes following segregation based on EGFR expression status (Supplementary Fig. S6B). ELOVL2 mRNA expression is elevated in the classic glioblastoma subtype, which is characterized by EGFR amplification and is defined, in part, through ELOVL2 expression (Supplementary Fig. S6C). Across multiple patient datasets, ELOVL2 and EGFR mRNA levels were highly correlated (Supplementary Fig. S6D). RNA-sequencing analysis following ELOVL2 knockdown in two patient-derived GSCs revealed altered expression in gene sets associated with cell-cycle progression and MAPK regulation, an important protumorigenic cascade linked to EGFR signaling (Fig. 6C; Supplementary Fig. S6E and S6F). To assess the effects of ELOVL2 knockdown on EGFR signaling, we analyzed EGFR expression at the mRNA and protein levels. Although mRNA levels of EGFR were not affected or even increased in several GSCs (Fig. 6D), knockdown of ELOVL2 decreased the levels of total EGFR protein, activated phosphorylated EGFR, and activated ERK (a downstream EGFR signaling element) in two GSCs (Fig. 6E), suggesting ELOVL2 regulates EGFR post-transcriptionally. These findings were further validated by targeting the ELOVL2 superenhancer using the dCas9-KRAB repression approach, indicating the ELOVL2 superenhancer supports EGFR signaling (Fig. 6F).

To assess the role of LC-PUFAs in EGFR signaling, cell culture media were supplemented with the LC-PUFA ELOVL2 products ω3-DHA and ω6-DPA, which induced EGFR signaling with increased phosphorylation of EGFR and activation of downstream ERK signaling (Fig. 6G). This effect was only observed 24 and 48 hours following addition of LC-PUFAs, suggesting that the fatty acids do not directly stimulate EGFR signaling elements, but rather must be metabolized first. These findings, together with our observations that ELOVL2 regulates EGFR signaling through a post-transcriptional mechanism and that ELOVL2 affects membrane phospholipid metabolism, prompted us to investigate the dynamics of EGFR membrane localization. EGFR stability and signaling are regulated through interactions with cellular membranes (32, 33). Using super-resolution stochastic optical reconstruction microscopy (STORM; Fig. 6H; Supplementary Fig. S6G) and flow cytometry (Fig. 6I; Supplementary Fig. S6H), we found that EGFR membrane localization and intensity decreased upon ELOVL2 knockdown. Targeting the ELOVL2 superenhancer element similarly reduced the sharp membrane localization and intensity of EGFR as visualized by immunofluorescence (Fig. 6J). LC-PUFA supplementation partially rescued EGFR phosphorylation following ELOVL2 knockdown, moderately enhanced ERK phosphorylation, and partially reduced PARP cleavage (Fig. 6K). These data suggest that ELOVL2 acts through regulation of membrane phospholipid dynamics in GSCs and supports efficient EGFR signaling.

Because many cellular processes are affected by cell membrane integrity, we investigated the potential for ELOVL2 to impact other RTKs beyond EGFR. In the TCGA, ELOVL2 mRNA levels were correlated with protein levels of EGFR, but were not correlated with other RTKs including IGF1R, MET, and KIT (Supplementary Fig. S6I). ELOVL2 knockdown by shRNA or the dCas9-KRAB superenhancer targeting system reduced protein abundance of several RTKs including HER2/ERBB2, PDGFRβ, FGFR1, and INSR, whereas levels of IGF1Rβ and DDR1 were relatively unchanged (Supplementary Fig. S6J–S6L). We utilized rescue approaches to determine the contributions of signaling elements downstream of ELOVL2. Overexpression of EGFR rescued the cell proliferation defects caused by ELOVL2 knockdown (Figs. 6L and M). Likewise, overexpression of a constitutive active form of MEK1 (S218D, S222D), which lies downstream of EGFR, partially rescued the ELOVL2-induced proliferation defect (Fig. 6N and O; Supplementary Fig. S6M). Treatment of GSCs with the known ERK activator lysophosphatidylethanolamine (LPE) partially rescued the ELOVL2 knockdown–associated cell proliferation defect, suggesting that inhibition of downstream EGFR signaling nodes contributes to the ELOVL2 knockdown phenotypes (Supplementary Fig. S6N). We further interrogated the localization of EGFR at a single-cell level. Quantification of EGFR density across the cell using STORM imaging revealed that ELOVL2 knockdown abolished the preferential localization of EGFR along the periphery of the cell in the cell membrane in two GSCs (Supplementary Fig. S7A–S7F). Collectively, these findings indicate that ELOVL2 maintains efficient EGFR signaling in GSCs through its LC-PUFA products.

To determine the clinical relevance of the LC-PUFA synthesis pathway, we interrogated a study of metabolite profiling in cancer tissues (34). World Health Organization (WHO) grade IV glioma tissues contained greater quantities of the direct products of ELOVL2, including adrenic acid, ω6-docosapentaenoic acid, and ω3-docosapentaenoic acid than WHO grade II gliomas (Fig. 7A). Lipid metabolism gene signatures, including those related to phospholipid biosynthesis and remodeling, were associated with poor clinical outcomes in the TCGA dataset (Fig. 7B; Supplementary Fig. S8A–S8C). Although no small molecules exist to specifically target ELOVL2, a small-molecule inhibitor of FADS2 (SC-26196) has been utilized in vitro and in vivo (35–37), although never in orthotopic glioblastoma models. FADS2 acts as a Δ-6 desaturase that catalyzes the enzymatic step immediately following ELOVL2 in the LC-PUFA synthesis cascade (Fig. 7C). We hypothesized that FADS2 would serve essential functions in GSCs, which depend on ELOVL2-mediated LC-PUFA synthesis. FADS2 was upregulated in glioblastoma tissue as compared with normal brain tissue, was epigenetically upregulated in GSCs as compared with DGCs, and was upregulated at the mRNA level in nine patient-derived GSCs compared with matched DGCs (Fig. 7D; Supplementary Fig. S8D and S8E). Depletion of FADS2 with three independent, nonoverlapping shRNAs greatly diminished cell proliferation capacity in two patient-derived GSCs, demonstrating its important functional role (Fig. 7E). Knockdown of FADS2 phenocopied ELOVL2 knockdown, as demonstrated by induction of apoptosis and depletion of EGFR activity and downstream signaling elements upon knockdown (Fig. 7F). In three GSCs, inhibition of FADS2 with SC-26196 impaired cell proliferation in a concentration-dependent manner, indicating that LC-PUFA synthesis enzymes play critical roles and can be targeted in glioblastoma (Fig. 7G).

The connection between LC-PUFA synthesis networks and EGFR signaling efficacy suggests that dual targeting of these nodes would impair cell proliferation in a combinatorial manner. Treatment of GSCs with varying concentrations of the EGFR inhibitor lapatinib and the FADS2 inhibitor SC-26196 showed that combinatorial treatment attenuated cell proliferation to a greater extent than either compound alone (Supplementary Figs. S8F). This interaction was synergistic in four patient-derived GSCs, with ZIP synergy scores ranging from 4.5 to 43 (for which scores greater than 1 indicate a synergistic interaction; Fig. 7H). The addition of SC-26196 to lapatinib further diminished EGFR phosphorylation and dampened ERK activation compared with lapatinib treatment alone, suggesting that SC-26196 may blunt compensatory signaling in response to lapatinib (Supplementary Fig. S8G). To explore the potential for ELOVL2 expression to predict sensitivity to EGFR inhibition in a pan-cancer setting, we queried the Cancer Therapeutics Response Portal, which contains data on 481 compounds tested across 860 cancer cell lines (38, 39). Low mRNA levels of ELOVL2 were associated with increased sensitivity to a variety of EGFR inhibitors, including afatinib, erlotinib, and lapatinib (Supplementary Fig. S8H). This is consistent with our finding that targeting LC-PUFA metabolism sensitizes GSCs to EGFR inhibition. The combination of SC-26196 and lapatinib did not display synergy in astrocytes or nonmalignant neural cells, suggesting specific effects in GSCs (Supplementary Fig. S8I).

Finally, we interrogated the potential for therapeutic targeting of LC-PUFA synthesis in an in vivo setting. Mice bearing orthotopic xenografts derived from patient-derived GSCs transduced with one of two independent shRNAs targeting ELOVL2 displayed a prolonged time to onset of neurologic signs compared with mice bearing GSCs transduced with a nontargeting shRNA control (shCONT), indicating that ELOVL2 knockdown impaired in vivo tumor formation capacity (Fig. 7I; Supplementary Fig. S8J). Histologic images from tumor-bearing brains show increased in vivo growth of tumors derived from GSCs transduced with shCONT, whereas tumors derived from GSCs transduced with either of two shRNAs targeting ELOVL2 were greatly reduced (Fig. 7I; Supplementary Fig. S8J). To address the potential for therapeutic targeting of ELOVL2 and LC-PUFA synthesis for glioblastoma, we utilized three approaches. As pharmacologic ELOVL2 inhibitors are not currently available, we genetically targeted ELOVL2 then interrogated the additional benefit of lapatinib. Survival of mice bearing xenografts derived from cells with shRNAs targeting ELOVL2 was further prolonged with lapatinib treatment (Supplementary Fig. S8K). Because of concerns regarding systemic toxicities and drug delivery, we treated GSCs prior to implantation into the brains of NSG mice. Combinatorial treatment of GSCs in vitro with SC-26196 and lapatinib extended the latency to tumor formation compared with vehicle control or single-agent therapies (Fig. 7J). Finally, we assessed the efficacy of the small-molecule FADS2 inhibitor SC-26196 to impair tumor growth in a preclinical setting in combination with lapatinib. Intracranial tumors were generated by implantation of patient-derived GSCs into the brains of mice. Seven days after implantation, daily treatment with 125 mg/kg of SC-26196 and/or 30 mg/kg of lapatinib was initiated. Each agent alone prolonged survival of mice bearing orthotopic xenografts (Fig. 7K). Treatment with a combination of the two agents prolonged survival compared with vehicle control, but induced additional toxicity, with hair thinning and weight loss (data not shown), with a nonstatistical trend toward improvement in survival over the monotherapies (Fig. 7K; Supplementary Fig. S8L). This suggests that careful modulation of drug dosages may allow for a combinatorial benefit while minimizing toxicities and provides a rationale to develop novel selective pharmacologic inhibitors for ELOVL2 and LC-PUFA synthesis enzymes. Collectively, these results suggest that LC-PUFA synthesis pathways represent a potential therapeutic target for future drug development.

Using a superenhancer profiling strategy, we now show that glioblastomas and GSCs epigenetically upregulate expression of ELOVL2 through activation of a noncoding regulatory region that is specific to GSCs. Superenhancers drive expression of genes essential for cancer cell survival in a number of cancer types, including in diffuse large B-cell lymphoma (29), T-cell acute lymphoblastic leukemia (40), and medulloblastoma (41), among others (10, 11). Our identification of ELOVL2 as a GSC-specific superenhancer-associated gene implicates the LC-PUFA synthesis network as a critical metabolic dependency in glioblastoma.

Fatty acids play a number of important roles in all cell types, including structural roles as components of the cell membrane in the form of phospholipids and cardiolipins. They also are components of key lipid signaling molecules, such as diacylglycerols, phosphotidylinositols (PIP family compounds), prostaglandins, leukotrienes, lysophosphatidic acid, and regulators of WNT–β-catenin signaling through acylation (42). In addition to the numerous well-documented instances of metabolic derangements present in tumor cells, fatty-acid metabolism is significantly altered in many cancer types (15). The key fatty-acid synthesis enzyme fatty acid synthase is upregulated in many human cancers (15) including breast cancer, prostate cancer, colon cancer, ovarian cancer, and glioma (43), among others, and is frequently associated with poor patient prognosis. Although normal tissues mainly rely on exogenous fatty acids for energetic and structural needs, cancer cells depend on endogenous fatty-acid synthesis for nearly all of their production of membrane phospholipids and energetic needs (44, 45) and frequently use alternative fuels (46).

The metabolic enzymes implicated in our study, ELOVL2 and FADS2, elongate and desaturate LC-PUFAs, respectively. It has been known for decades that glioblastoma tissues contain higher free fatty acid, LC-PUFAs, and altered phospholipid composition as compared with normal brain tissue (16, 47). However, the precise roles for these fatty acids are more complex. In ovarian cancer, unsaturated fatty acids were found to be enriched in cancer stem cells with inhibition of fatty-acid desaturases resulting in impaired tumor initiation capacity (48). Other reports have indicated that LC-PUFAs are cytotoxic to glioblastoma cells (49). It is likely that the effects of these fatty acids are both context- and concentration-dependent. One major role for fatty-acid synthesis in glioblastoma is the connection between oncogenic signaling pathways and reprogramming of cellular metabolism. mTOR signaling has been shown to upregulate de novo fatty-acid synthesis to promote hepatocellular carcinoma progression (50). EGFR signaling in glioblastoma upregulates SREBP1, a key transcription factor that drives expression of lipogenic genes, and this relationship establishes a synthetic lethality between activated EGFR and lipid metabolism enzymes (17, 18, 21, 22). Our results complement and build on this model by suggesting a positive feedback loop whereby LC-PUFA synthesis supports efficient EGFR signaling through preservation of cellular membrane structure. Other studies have linked fatty-acid metabolites, including prostaglandin E2 and leukotrienes, as regulators of EGFR signaling (51, 52), and fatty-acid metabolites may potentiate EGFR signaling through post-translational modifications (53). As the most commonly amplified oncogene in glioblastoma, EGFR has served as a target for numerous preclinical and clinical trials for the treatment of glioblastoma. However, EGFR-targeting agents have invariably failed to extend patient survival. Our data suggest that combinatorial approaches targeting both EGFR signaling elements as well as LC-PUFA synthesis may enhance therapeutic efficacy. In summary, we utilized a superenhancer screening approach that implicated ELOVL2 as a critical epigenetically driven dependency in glioblastoma. ELOVL2 promotes LC-PUFA synthesis, which is essential for the maintenance of cellular membrane architecture and which supports efficient EGFR signaling (Supplementary Fig. S8M). In conclusion, our results suggest that aberrant chromatin regulation in cancer can drive oncogenic signal transduction through dysregulation of metabolic pathways that contribute to membrane dynamics, offering novel combinatorial strategies for lethal cancers.

Glioblastoma tissues were obtained from excess surgical resection samples from patients at Duke University or Case Western Reserve University (Cleveland, OH) after review by neuropathology with appropriate consent and in accordance with an Institutional Review Board–approved protocol (090401). All patient studies were conducted in accordance with the Declaration of Helsinki. GSC387 and GSC3565 were derived by our laboratory and transferred via a material transfer agreement from Duke University (Durham, NC). MGG4, MGG6, and MGG8 were a kind gift of Hiroaki Wakimoto and obtained via a material transfer agreement from Massachusetts General Hospital. GSC2012, GSC1919, GSC-CW738, GSC1517, GSC3264, GSC3028, and GSC3136 were derived by our laboratory as reported previously. GSC23 was transferred via a material transfer agreement from The University of Texas MD Anderson Cancer Center (Houston, TX). All GSCs were cultured in Neurobasal media (Invitrogen) supplemented with B27 without vitamin A (Invitrogen), EGF, and bFGF (20 ng/mL each; R&D Systems), sodium pyruvate, and Glutamax. To decrease the incidence of cell culture–based artifacts, patient-derived xenografts were produced and propagated as a renewable source of tumor cells for study. Short tandem repeat analyses were performed to authenticate the identity of each tumor model used in this article on a yearly basis. Cells were stored at −160°C when not being actively cultured. Mycoplasma testing was performed by qPCR cellular supernatants on a yearly basis. Cells were grown for fewer than 20 in vitro passages from xenografts.

The nonmalignant neural stem cell models ENSA, hNP1, and NSC11 were used in this study. ENSA (ENStem-A) is a human embryonic stem–derived neural progenitor cell (Millipore Sigma, catalog no. SCC003). NSC11 is a human-induced pluripotent-derived neural progenitor cell (Alstem, catalog no. hNSC11). hNP1 (STEMEZhNP1) is a human neural progenitor cell (Neuromics, catalog no. HN60001). The nonmalignant neural cells (NM53, NM55, NM176, and NM263) were derived from excess surgical resection tissue from patients undergoing surgery for epilepsy. Human astrocyte #1 was obtained from Thermo Fisher Scientific/Gibco (catalog no. N7805200). Human astrocyte #2 was obtained from ScienCell (catalog no. 1800).

For ELOVL2 shRNA experiments, intracranial xenografts were generated by implanting 10,000 human-derived GSCs into the right cerebral cortex of NSG mice (NOD.Cg-Prkdc^scid Il2rg^tm1Wjl/SzJ; The Jackson Laboratory) at a depth of 3.5 mm under a University of California, San Diego, Institutional Animal Care and Use Committee–approved protocol.

For in vivo drug combination studies, intracranial xenografts were generated by implanting 1,000 patient-derived GSCs (GSC387) into the right cerebral cortex of NSG mice as described above. Mice recovered for 7 days and were then treated daily with vehicle (0.5% methylcellulose), 125 mg/kg SC-26916, 30 mg/kg lapatinib, or a premixed combination of 125 mg/kg SC-26916 and 30 mg/kg lapatinib by oral gavage.

For experiments investigating the effects of lapatinib treatment in mice implanted with shRNA knockdown cells, intracranial xenografts were generated by implanting 1,000 patient-derived GSCs (GSC387) transduced with either an shRNA targeting ELOVL2 (shELOVL2.308) or a nontargeting shRNA control into the right cerebral cortex of NSG mice as described above. Mice recovered for 7 days and were then treated daily with either vehicle (0.5% methylcellulose), 20 mg/kg lapatinib, or 40 mg/kg lapatinib by oral gavage.

For experiments interrogating the effects of combinatorial treatment on in vivo tumor formation capacity, GSCs (GSC387) were cultured in vitro and treated with either vehicle (DMSO), 10 μmol/L SC-26916, 5 μmol/L lapatinib, or a combination of 10 μmol/L SC-26916 and 5 μmol/L lapatinib for two days prior to implantation. Intracranial xenografts were generated by implanting 5,000 cells from one of the four conditions into the right cerebral cortex of NSG mice as described above.

All murine experiments were performed under an animal protocol approved by the University of California, San Diego, Institutional Animal Care and Use Committee. Healthy, wild-type male or female mice of NSG background, 4 to 6 weeks old, were randomly selected and used in this study for intracranial injection. Mice had not undergone prior treatment or procedures. Mice were maintained in 14-hour light/10-hour dark cycle by animal husbandry staff with no more than 5 mice per cage. Experimental animals were housed together. Housing conditions and animal status were supervised by a veterinarian. Animals were monitored until neurologic signs were observed, at which point they were sacrificed. Neurologic signs or signs of morbidity included hunched posture, gait changes, lethargy, and weight loss. Brains were harvested and fixed in 4% formaldehyde for 48 hours, stored at 4°C in 70% ethanol, and sectioned. Hematoxylin and eosin staining was performed on sections for histologic analysis.

For complete experimental details, see Supplementary Sections S1 and S2.

All statistical analyses are described in the figure legends. For TCGA glioblastoma versus normal brain RNA-sequencing calculations, four-way ANOVA controlling for sex, age, and ethnicity with Benjamini and Hochberg FDR method was used for statistical analysis. For survival analyses, the Cox proportional hazards and log-rank analyses were used. For qPCR analyses, Student t test was used to assess statistical significance, when appropriate. Two-way repeated-measures ANOVA was used for statistical analysis with Dunnett multiple hypothesis test correction. For proliferation assays, two-way repeated-measures ANOVA was used for statistical analysis with Dunnett multiple hypothesis test correction.

All newly generated raw sequencing data related to this study (related to ELOVL2 knockdown RNA sequencing) is available on GEO through accession number GSE130648. All data accessed from external sources and prior publications have been referenced in the text and corresponding figure legends. Additional data will be made available upon request.

P.S. Mischel has ownership interest (including stock, patents, etc.) in Pretzel Therapeutics and is a consultant/advisory board member for the same. No potential conflicts of interest were disclosed by the other authors.

Conception and design: R.C. Gimple, P.S. Mischel, S.C. Mack, Q. Xie, J.N. Rich

Development of methodology: R.C. Gimple, Q. Wu, J. Bi, H. Cang, T. Huan, Q. Xie, J.N. Rich

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): R.C. Gimple, R.L. Kidwell, A.D. Gromovsky, Q. Wu, D. Lv, B.C. Prager, L. Zhao, D. Lee, A.E. Sloan, J.M. Brown, T. Huan

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): R.C. Gimple, R.L. Kidwell, L.J.Y. Kim, T. Sun, A.D. Gromovsky, Q. Ye, Z. Zhu, A.E. Sloan, J.M. Brown, T. Huan, Q. Xie, J.N. Rich

Writing, review, and/or revision of the manuscript: R.C. Gimple, R.L. Kidwell, A.E. Sloan, P.S. Mischel, H. Cang, T. Huan, Q. Xie, J.N. Rich

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): L.J.Y. Kim, M. Wolf, S. Bhargava, L. Jiang, X. Wang, Z. Zhu, G. Zhang, Z. Dong, D. Lee, J. Bi, A.E. Sloan, Q. Xie, J.N. Rich

Study supervision: Z. Zhu, H. Cang, Q. Xie, J.N. Rich

This work was supported by grants provided by NIH: CA217065, to R.C. Gimple; CA203101, to L.J.Y. Kim; CA217066, to B.C. Prager; CA197718, CA154130, CA169117, CA171652, NS087913, NS089272, and NS103434, to J.N. Rich; R01 HL122283, P50 AA024333, 4UL1TR000439, P30 CA043703, and VeloSano Foundation, to J.M. Brown; CPRIT award, ALSF young investigator award, Rally research grant, BEAR Necessities Pediatric Cancer Foundation Grant, Children's Cancer Research Fund award, and Baylor College of Medicine Junior Faculty Award (to S.C. Mack); NS073831 (to P.S. Mischel); NIH New Innovator Award 1-DP2-EB020400 (to H. Cang); A217956-01, CA187780, and NS 089272 as well as the Coulter, Ferry Foundation, Kimble and Gerald Kaufman Jr. Foundations and the Peter D. Cristal Chair at University Hospitals (to A.E. Sloan). This study was partially supported by a University of British Columbia Start-up Grant awarded to T. Huan. We thank the National Institute of Mental Health Chemical Synthesis and Drug Supply Program for providing us with the SC-26196 drug. We thank Chengwei He, PhD, for assistance in developing in vivo treatment protocols with SC-26196. We thank Renliang Zhang, PhD, for assistance in total fatty-acid quantification. Supplementary Fig. S8M was prepared in part using images from Servier Medical Art by Servier (https://smart.servier.com/), which is licensed under a Creative Commons Attribution 3.0 Unported License (https://creativecommons.org/licenses/by/3.0/).

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